166
9.3 Description of Study Area
Barasat I CD (community development) block has been taken as the case study area
which is situated at the north-east portion of the Kolkata Metropolitan Area (KMA).
This study area consists of two municipalities, i.e. Barasat and Madhyamgram.
Barasat Municipality is the district headquarter of North 24 Parganas. Geographically,
the study area is situated in the lower Gangetic plain and located at 22°40′00″ N to
22°50′00″ N latitudes and 88°25′00″E to 88°35′00″E longitude. Literature reviews
show that the growth of Kolkata city is expanding more towards the north-east part.
Moreover, municipalities are growing at a faster rate, and the villages are also converted into urban area unprecedentedly. According to Basu and Saha (2017) Barasat
Municipality is one of the most growing cities in West Bengal. Climatically, the
study area is experiencing tropical dry-wet climate and receiving 1800 mm rainfall
per year. The annual maximum mean temperature is 31.7 °C and minimum mean
temperature is 22.2 °C (Fig. 9.1).
9.4 Databases and Methodology
Nowadays, the best way to extract land use/land cover information is by using satellite images (Brondizio et al. 1994; Yuan et al. 2005; Rawat and Kumar 2015). In the
present study, varied data sets were employed to carry out the work including census data and Indian multi-temporal satellite images (OLI_TIRS) with 30 meter spatial resolution downloaded from the USGS web site (http://earthexplorer.usgs.gov)
for the year 1990 (TM), 2000 (ETM+), 2010 (TM) and 2017 to extract the built-up
growth and land use change. All images were already geometrically corrected and
developed in standard projection (UTM 45 N, WGS84 datum). Images were collected in the months of November, December and January which is in the winter
period that is why the seasonal variation is insignificant.
Population-related data has been collected from the various published journals,
books, and Census of India for the years 1991, 2001 and 2011. Through the population data density, urban population growth has been calculated to analyse urbanization in terms of population increase. CD block and village-wise population data are
also used to show the differences between the urban area and rural area.
Various statistic techniques are used to measure urban sprawl. Here, an attempt
has been made to find out the different properties of growth.
Observed built-up area has been calculated based on percentage growth rate
which is presented in Table 9.4.
The expected growth of built-up area has been calculated by using equation
(9.1), presented in Table 9.5, which is considered as the M matrix with element M ij ,
where i = 1, 2, … n (analysis in specific time span, row total) and j = 1, 2, … n
(specific zone, column total). The expected growth of impervious area is computed
by multiplying the marginal total divided by the grand total (Almeida et al. 2005):
Rukhsana and Md. Hasnine
9.3 Description of Study Area
Barasat I CD (community development) block has been taken as the case study area
which is situated at the north-east portion of the Kolkata Metropolitan Area (KMA).
This study area consists of two municipalities, i.e. Barasat and Madhyamgram.
Barasat Municipality is the district headquarter of North 24 Parganas. Geographically,
the study area is situated in the lower Gangetic plain and located at 22°40′00″ N to
22°50′00″ N latitudes and 88°25′00″E to 88°35′00″E longitude. Literature reviews
show that the growth of Kolkata city is expanding more towards the north-east part.
Moreover, municipalities are growing at a faster rate, and the villages are also converted into urban area unprecedentedly. According to Basu and Saha (2017) Barasat
Municipality is one of the most growing cities in West Bengal. Climatically, the
study area is experiencing tropical dry-wet climate and receiving 1800 mm rainfall
per year. The annual maximum mean temperature is 31.7 °C and minimum mean
temperature is 22.2 °C (Fig. 9.1).
9.4 Databases and Methodology
Nowadays, the best way to extract land use/land cover information is by using satellite images (Brondizio et al. 1994; Yuan et al. 2005; Rawat and Kumar 2015). In the
present study, varied data sets were employed to carry out the work including census data and Indian multi-temporal satellite images (OLI_TIRS) with 30 meter spatial resolution downloaded from the USGS web site (http://earthexplorer.usgs.gov)
for the year 1990 (TM), 2000 (ETM+), 2010 (TM) and 2017 to extract the built-up
growth and land use change. All images were already geometrically corrected and
developed in standard projection (UTM 45 N, WGS84 datum). Images were collected in the months of November, December and January which is in the winter
period that is why the seasonal variation is insignificant.
Population-related data has been collected from the various published journals,
books, and Census of India for the years 1991, 2001 and 2011. Through the population data density, urban population growth has been calculated to analyse urbanization in terms of population increase. CD block and village-wise population data are
also used to show the differences between the urban area and rural area.
Various statistic techniques are used to measure urban sprawl. Here, an attempt
has been made to find out the different properties of growth.
Observed built-up area has been calculated based on percentage growth rate
which is presented in Table 9.4.
The expected growth of built-up area has been calculated by using equation
(9.1), presented in Table 9.5, which is considered as the M matrix with element M ij ,
where i = 1, 2, … n (analysis in specific time span, row total) and j = 1, 2, … n
(specific zone, column total). The expected growth of impervious area is computed
by multiplying the marginal total divided by the grand total (Almeida et al. 2005):
Rukhsana and Md. Hasnine